Program taking forever to run [closed] - java

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public class Problem_3 {
public static void main(String... args) {
long limit = 600851475143L;
long largestPrimeFactor = 0;
for (long number = 2; number < limit; number++) {
if (isPrime(number)) {
if ((limit % number == 0)){
largestPrimeFactor = number;
}
}
}
System.out.println(largestPrimeFactor);
}
public static boolean isPrime(long number) {
for (int i = 2; i < number; i++) {
if (number % i == 0) {
return false;
}
}
return true;
}
}
I'm sure, the above program is not in infinite loop. I tested with limit = 13195; and got desired result 29
I don't understand why my CPU is taking forever to run it.
EDIT:
Its my code for ProjectEuler.net problem number 3.

Your algorithm has a time complexity of O(n^2), making it not very effective for larger values of your limit.
So it's slow because you're using a poor algorithm.

Time complexity of your code is O(N^2). So it's not a good algorithm for large numbers. A possible suggestion would be as follows -
You are interested in largest prime factor then why not start from the largest value?
for (long number = limit-1; number > 1; number--) {
if (isPrime(number)) {
if ((limit % number == 0)){
largestPrimeFactor = number;
break;
}
}
}
Though time complexity remains the same this would definitely reduce your time than your present algorithm.
But, what exactly is time complexity..?? and how do u calculate it..?? and what is O(N^2) ?? please explain
for (long number = 2; number < limit; number++)
Above is your first for loop in which you will have n iterations. Inside this you call isPrime() function which again has a for loop in it for (int i = 2; i < number; i++) again having n iterations. So basically you have two for loops one inside the other which makes your time complexity n*n = n^2

This is the reason.
long limit = 600851475143L;
and an O(n^2) algorithm and n is this long number 600851475143L

you are passing each no to the isPrime(long number) method & again you have taken the for loop "for (int i = 2; i < number; i++) {" which is running for another (number-1) every times. means you are running this 600851475141*600851475141 times.
You could have an idea how much time it will take ...........may be you need a super comp for this.....
Happy coding

Because of the nesting of your loops (one loop up to limit in main and another loop called from within that loop, within isPrime) the time complexity of your algorithm is O(n^2).
This is a standard way to express how long an algorithm takes to solve a different problem for different sized inputs.
In your case, the size is the limit (600851475143L) so to solve the problem up to this will take "an order of 600851475143 ^ 2", compared to, "10 ^ 2 (i.e. 100)", if you had a limit of 10 (for example)
So if the version with a limit of 10 took 100 milliseconds (10 squared), your 600851475143 version would take something like 361022495181519000000000 milliseconds (i.e. 600851475143L squared, apologies if I got some zeroes wrong there)
Other examples of time complexity would be O(1), or constant time, where the algorithm takes the same time regardless of the size, or O(n), or linear time, where the time taken is directly proportional to the size

As all said your code is not very time efficient but looking at the code i can guess that you are working to find the biggest prime factor to do that you can actually try Sieve of Eratosthenes to generate all prime then find the factor from back.
import java.util.LinkedList;
class Sieve{
public static LinkedList<Long> sieve(long n){
if(n < 2) return new LinkedList<Long>();
LinkedList<Long> primes = new LinkedList<Long>();
LinkedList<Long> nums = new LinkedList<Long>();
for(long i = 2;i <= n;i++){ //unoptimized
nums.add(i);
}
while(nums.size() > 0){
long nextPrime = nums.remove();
for(long i = nextPrime * nextPrime;i <= n;i += nextPrime){
nums.removeFirstOccurrence(i);
}
primes.add(nextPrime);
}
return primes;
}
}
the above code returns the linked list of prime numbers use this start from last and get your largest factor.
NOTE:increase the heap size of jvm before running for the input of 600851475143L

Related

Possible multiplications of k distinct factors with largest possible factor n

Let M(n,k) be the sum of all possible multiplications of k distinct factors with largest possible factor n, where order is irrelevant.
For example, M(5,3) = 225 , because:
1*2*3 = 6
1*2*4 = 8
1*2*5 = 10
1*3*4 = 12
1*3*5 = 15
1*4*5 = 20
2*3*4 = 24
2*3*5 = 30
2*4*5 = 40
3*4*5 = 60
6+8+10+12+15+20+24+30+40+60 = 225.
One can easily notice that there are C(n,k) such multiplications, corresponding to the number of ways one can pick k objects out of n possible objects. In the example above, C(5,3) = 10 and there really are 10 such multiplications, stated above.
The question can also be visualized as possible n-sized sets containing exactly k 0's, where each cell that does not contain 0 inside it, has the value of its index+1 inside it. For example, one possible such set is {0,2,3,0,5}. From here on, one needs to multiply the values in the set that are different than 0.
My approach is a recursive algorithm. Similiarly to the above definition of
M(n,k), I define M(n,j,k) to be the sum of all possible multiplications of exactly k distinct factors with largest possible factor n, AND SMALLEST possible factor j. Hence, my approach would yield the desired value if ran on
M(n,1,k). So I start my recursion on M(n,1,k), with the following code, written in Java:
public static long M (long n, long j, long k)
{
if (k==1)
return usefulFunctions.sum(j, n);
for (long i=j;i<=n-k+1+1;i++)
return i*M(n,i+1,k-1);
}
Explanation to the code:
Starting with, for example, n=5 , j=1, k=3, the algorithm will continue to run as long as we need more factors, (k>=1), and it is made sure to run only distinct factors thanks to the for loop, which increases the minimal possible value j as more factors are added. The loop runs and decreases the number of needed factors as they are 'added', which is achieved through applying
M(n,j+1,k-1). The j+1 assures that the factors will be distinct because the minimal value of the factor increases, and k-1 symbolizes that we need 1 less factor to add.
The function 'sum(j,n)' returns the value of the sum of all numbers starting from j untill n, so sum(1,10)=55. This is done with a proper, elegant and simple mathematical formula, with no loops: sum(j,n) = (n+1)*n/2 - (i-1)*i/2
public static long sum (long i, long n)
{
final long s1 = n * (n + 1) / 2;
final long s2 = i * (i - 1) / 2;
return s1 - s2 ;
}
The reason to apply this sum when k=1, I will explain with an example:
Say we have started with 1*2. Now we need a third factor, which can be either of 3,4,5. Because all multiplications: 1*2*3, 1*2*4, 1*2*5 are valid, we can return 1*2*(3+4+5) = 1*2*sum(3,5) = 24.
Similiar logic explains the coefficient "i" next to the M(n,j+1,k-1).
say we have now the sole factor 2. Hence we need 2 more factors, so we multiply 2 by the next itterations, which should result in:
2*(3*sum(4,5) + 4*sum(5,5))
However, for a reason I can't explain yet, the code doesn't work. It returns wrong values and also has "return" issues that cause the function not to return anything, don't know why.
This is the reason i'm posting this question here, in hope someone will aid me. Either by fixing this code or sharing a code of his own. Explaining where I'm going wrong will be most appreciable.
Thanks a lot in advance, and sorry for this very long question,
Matan.
-----------------------EDIT------------------------
Below is my fixed code, which solves this question. Posting it incase one should ever need it :) Have fun !
public static long M(long n, long j, long k)
{
if (k == 0)
return 0;
if (k == 1)
return sum(j,n);
else
{
long summation = 0;
for (long i=j; i<=n; i++)
summation += i*M(n, i+1, k-1);
return summation;
}
}
I see that u got ur answer and i really like ur algorithm but i cant control myself posting a better algorithm . here is the idea
M(n,k) = coefficient of x^k in (1+x)(1+2*x)(1+3*x)...(1+n*x)
u can solve above expression by divide and conquer algorithm Click Here to find how to multiply above expression and get polynomial function in the form of ax^n + bx^(n-1)....+c
overall algorithm time complexity is O(n * log^2 n)
and best part of above algorithm is
in the attempt of finding solution for M(n,k) , u will find solution for M(n,x) where 1<=x<=n
i hope it will be useful to know :)
I am not sure about your algorithm, but you certainly messed up with your sum function. The problem you have is connected to type casting and division of integer numbers. Try something like this:
public static long sum (long i, long n)
{
final long s1 = n * (n + 1) / 2;
final long s2 = (i * i - i) / 2;
return s1 - s2 ;
}
You have a problem with your sum function : here is the correct formula:
public static long sum (long i, long n)
{
double s1 = n*(n+1)/2;
double s2 = i*(i-1)/2;
return (long)(s1-s2);
}
Here the full solution :
static int n = 5;
static long k = 3;
// no need to add n and k them inside your M function cause they are fixed.
public static long M (long start) // start = 1
{
if(start > k) // if start is superior to k : like your example going from 1..3 , then you return 0
return 0;
int res = 0; // res of your function
for(long i=start+1;i<n;i++){
res+=start*i*sum(i+1,n); // here you take for example 1*2*sum(3,5) + 1*3*sum(4,5).... ect
}
return res+M(start+1); // return res and start again from start+1 wich would be 2.
}
public static long sum (long i, long n)
{
if(i>n)
return 0;
double s1 = n*(n+1)/2;
double s2 = i*(i-1)/2;
return (long)(s1-s2);
}
public static void main(String[] args) {
System.out.println(M(1));
}
Hope it helped

A simple java program to find the largest prime factor of a large number(here 600851475143) compiled with no errors but not giving any output [closed]

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Closed 8 years ago.
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I'm not finding any fault with my program. Please point out my mistake and help me.
Code is written below:
class largest
{
public static void main(String...args)
{
double n,i,f=1.0;
n=600851475143L;
largest ob= new largest();
for(i=n/4;i<n/2;i++)
{
if(n%i==0)
{
if(ob.isprime(i) == 1)
f=i;
}
}
System.out.println(f);
}
int isprime(double k)
{
int s,i=2,flag=0;
while(i<k && flag==0)
{
if(k%i==0)
flag=1;
}
if(flag==0)
return 1;
else
return 0;
}
}
Your function isprime is in most cases an endless loop. It never increments i in the loop.
Every time you write a loop, you should think about the so called loop variant. This is numerical property of the loop, that is both:
A positive integer in each loop run
Decreasing during successive iterations of the loop
If you cannot think about such a property, you are in big trouble, because you have very likely an endless loop.
In your example, that property should be the number whose prime factor you want minus the current prime factor candidate you are checking.
In your current code, if you calculate the loop variant, you will get a positive integer (good), but it will not decrease (bad). As an consequence, you will wait forever, because you have an endless loop.
While other answers show nice solutions to make your code more efficient, this won't help you very much: an efficient endless loop still won't give you any result.
Your code is far too slow, that's why it takes so much time to execute and doesn't return any output (apparently). You should speed up your isPrime test using the following trick : if n is not a prime, it can be written as n = p x q where p <= sqrt(n) and q > p. Then, you can stop your loop at sqrt(n) since you are able to tell that n is not a prime if there is no integer p <= sqrt(n) verifying this property.
The following code uses that remark but also another property : a integer can always be written as 6*p + q where p and q are integers and q < 6. For all p, 6*p + 2 and 6*p + 4 are divisible by 2 and 6*p + 3 is divisible by 3 so for all n = 6*p + q, if n is not divisible by 2 nor by 3, then n has the form 6*p + 1 of 6*p + 5 (or 6*p - 1, which is equivalent).
public static boolean isPrime(int n) {
if (n == 2 || n == 3)
return true;
if(n <= 1 || n % 2 == 0 || n % 3 == 0)
return false;
int x = (int) Math.sqrt(n);
for(int i=1 ; (6*i-1) <= x ; i++)
if(n % (6*i-1) == 0 || n % (6*i+1) == 0)
return false;
return true;
}
Edit :
Plus, as stefan.schwetschke observed, you are not incrementing the index of your loop. In this case you should use a for loop since you now exactly the bounds of the index of the loop.
This is not a "code" answer (none of the other answers will provide a solution in a reasonable amount of time , even when correcting your brute force original code).
You may want to explore prime factorization algorithms, with Pollard-Strassen algorithm (or Rho Pollard algorithm).
Some research links include:
Wolfram Research http://mathworld.wolfram.com/PollardRhoFactorizationMethod.html
Colorado State University lecture http://www.cs.colorado.edu/~srirams/classes/doku.php/pollard_rho_tutorial
and here https://math.stackexchange.com/questions/185524/pollard-strassen-algorithm
(for mathematics on stackexchange.

Project Euler 12 - Optimization [closed]

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I am working on Project Euler Problem 12. Could anyone provide any tips on how to improve my code so it executes in my life time?
public class HighlyDivisibleTriangularNumber {
public static void main(String[] args) {
int divisors = 0;
int count = 1;
while(divisors <= 501) {
long triNum = triangularNumber(count);
divisors = getFactors(triNum);
System.out.println(triNum+"_"+divisors);
count++;
}
}
private static int getFactors(long triNum) {
int divisors = 0;
while(triNum > 1) {
triNum = triNum / 2;
divisors++;
}
return divisors;
}
private static long triangularNumber(int i) {
long total = 0;
for(int k = 1; k <= i; k++) {
total += k;
}
return total;
}
}
1) triangular numbers
The first (and probably most important) optimization you can do is in how you compute the triangular numbers.
You can observe that the nth triangular number (let's call it t(n) ) is equal to n + t(n-1).
So each time you compute a triangular number, you can just take the triangular number before it and add n. This would lead to the naive recursive function :
private static long triangularNumber(int i) {
if(i == 1) return 1;
else return i+triangularNumber(i-1);
}
But this won't improve the performance much... to resolve this, I suggest you do some research on memoization and adapt the function I gave you (I won't give you the answer, this is an excellent exercise)
Now, on a regular computer you should have the answer to the problem in a reasonable time. But it can be improved a little better
2) counting divisors
Your function for counting divisors is wrong. What you should do is try to divide your number by successive natural numbers and see if the result is an natural integer.
private static int getFactors(long triNum) {
int divisors = 0;
for(int i = 1; i <= triNum; ++i) {
if(triNum%i == 0) // triNum is a multiple of 1 <=> i is a divisor of triNum
divisors++;
}
return divisors;
}
You can even improve this by counting only to the square root of trinum and adding two divisors each time. But there's a trick if you do this, I'll let you figure it out if you decide to try this.
Why do do recompute the triNum each time? Just add the difference each time (basically your count).
public static void main(String[] args) {
int divisors = 0;
int count = 1;
long truNum = 0;
while(divisors <= 501) {
triNum += count;
divisors = getFactors(triNum);
System.out.println(triNum+"_"+divisors);
count++;
}
}
Furthermore, your approach to count the factors is completely off. You are just searching for the first power of two to be greater than the given number. Read up on (prime)-factorization. Note that you need to account for the combinations of (prime) factors, too.
Example: 12
12 = 2 * 2 * 3
But the divisors of 12 are
1, 2, 3, 4 (= 2*2), 6 (= 2*3), 12
So in total there are 6 divisors of 12 and not 3 as the mere prime factorization may lead you to believe.

Prime factorization algorithm fails for big numbers

I have run into a weird issue for problem 3 of Project Euler. The program works for other numbers that are small, like 13195, but it throws this error when I try to crunch a big number like 600851475143:
Exception in thread "main" java.lang.ArithmeticException: / by zero
at euler3.Euler3.main(Euler3.java:16)
Here's my code:
//Number whose prime factors will be determined
long num = 600851475143L;
//Declaration of variables
ArrayList factorsList = new ArrayList();
ArrayList primeFactorsList = new ArrayList();
//Generates a list of factors
for (int i = 2; i < num; i++)
{
if (num % i == 0)
{
factorsList.add(i);
}
}
//If the integer(s) in the factorsList are divisable by any number between 1
//and the integer itself (non-inclusive), it gets replaced by a zero
for (int i = 0; i < factorsList.size(); i++)
{
for (int j = 2; j < (Integer) factorsList.get(i); j++)
{
if ((Integer) factorsList.get(i) % j == 0)
{
factorsList.set(i, 0);
}
}
}
//Transfers all non-zero numbers into a new list called primeFactorsList
for (int i = 0; i < factorsList.size(); i++)
{
if ((Integer) factorsList.get(i) != 0)
{
primeFactorsList.add(factorsList.get(i));
}
}
Why is it only big numbers that cause this error?
Your code is just using Integer, which is a 32-bit type with a maximum value of 2147483647. It's unsurprising that it's failing when used for numbers much bigger than that. Note that your initial loop uses int as the loop variable, so would actually loop forever if it didn't throw an exception. The value of i will go from the 2147483647 to -2147483648 and continue.
Use BigInteger to handle arbitrarily large values, or Long if you're happy with a limited range but a larger one. (The maximum value of long / Long is 9223372036854775807L.)
However, I doubt that this is really the approach that's expected... it's going to take a long time for big numbers like that.
Not sure if it's the case as I don't know which line is which - but I notice your first loop uses an int.
//Generates a list of factors
for (int i = 2; i < num; i++)
{
if (num % i == 0)
{
factorsList.add(i);
}
}
As num is a long, its possible that num > Integer.MAX_INT and your loop is wrapping around to negative at MAX_INT then looping until 0, giving you a num % 0 operation.
Why does your solution not work?
Well numbers are discrete in hardware. Discrete means thy have a min and max values. Java uses two's complement, to store negative values, so 2147483647+1 == -2147483648. This is because for type int, max value is 2147483647. And doing this is called overflow.
It seems as if you have an overflow bug. Iterable value i first becomes negative, and eventually 0, thus you get java.lang.ArithmeticException: / by zero. If your computer can loop 10 million statements a second, this would take 1h 10min to reproduce, so I leave it as assumption an not a proof.
This is also reason trivially simple statements like a+b can produce bugs.
How to fix it?
package margusmartseppcode.From_1_to_9;
public class Problem_3 {
static long lpf(long nr) {
long max = 0;
for (long i = 2; i <= nr / i; i++)
while (nr % i == 0) {
max = i;
nr = nr / i;
}
return nr > 1 ? nr : max;
}
public static void main(String[] args) {
System.out.println(lpf(600851475143L));
}
}
You might think: "So how does this work?"
Well my tough process went like:
(Dynamical programming approach) If i had list of primes x {2,3,5,7,11,13,17, ...} up to value xi > nr / 2, then finding largest prime factor is trivial:
I start from the largest prime, and start testing if devision reminder with my number is zero, if it is, then that is the answer.
If after looping all the elements, I did not find my answer, my number must be a prime itself.
(Brute force, with filters) I assumed, that
my numbers largest prime factor is small (under 10 million).
if my numbers is a multiple of some number, then I can reduce loop size by that multiple.
I used the second approach here.
Note however, that if my number would be just little off and one of {600851475013, 600851475053, 600851475067, 600851475149, 600851475151}, then my approach assumptions would fail and program would take ridiculously long time to run. If computer could execute 10m statements per second it would take 6.954 days, to find the right answer.
In your brute force approach, just generating a list of factors would take longer - assuming you do not run out of memory before.
Is there a better way?
Sure, in Mathematica you could write it as:
P3[x_] := FactorInteger[x][[-1, 1]]
P3[600851475143]
or just FactorInteger[600851475143], and lookup the largest value.
This works because in Mathematica you have arbitrary size integers. Java also has arbitrary size integer class called BigInteger.
Apart from the BigInteger problem mentioned by Jon Skeet, note the following:
you only need to test factors up to sqrt(num)
each time you find a factor, divide num by that factor, and then test that factor again
there's really no need to use a collection to store the primes in advance
My solution (which was originally written in Perl) would look something like this in Java:
long n = 600851475143L; // the original input
long s = (long)Math.sqrt(n); // no need to test numbers larger than this
long f = 2; // the smallest factor to test
do {
if (n % f == 0) { // check we have a factor
n /= f; // this is our new number to test
s = (long)Math.sqrt(n); // and our range is smaller again
} else { // find next possible divisor
f = (f == 2) ? 3 : f + 2;
}
} while (f < s); // required result is in "n"

Java - Can't make ProjectEuler 3 Work for a very big number (600851475143)

Resolution:
It turns out there is (probably) "nothing wrong" with the code itself; it is just inefficient. If my math is correct, If I leave it running it will be done by Friday, October 14, 2011. I'll let you know!
Warning: this may contain spoilers if you are trying to solve Project Euler #3.
The problem says this:
The prime factors of 13195 are 5, 7, 13 and 29.
What is the largest prime factor of the number 600851475143 ?
Here's my attempt to solve it. I'm just starting with Java and programming in general, and I know this isn't the nicest or most efficient solution.
import java.util.ArrayList;
public class Improved {
public static void main(String[] args) {
long number = 600851475143L;
// long number = 13195L;
long check = number - 1;
boolean prime = true;
ArrayList<Number> allPrimes = new ArrayList<Number>();
do {
for (long i = check - 1; i > 2; i--) {
if (check % i == 0) {
prime = false;
}
}
if (prime == true && number % check == 0) {
allPrimes.add(check);
}
prime = true;
check--;
} while (check > 2);
System.out.println(allPrimes);
}
}
When number is set to 13195, the program works just fine, producing the result [29, 13, 7, 5] as it should.
Why doesn't this work for larger values of number?
Closely related (but not dupe): "Integer number too large" error message for 600851475143
The code is very slow; it is probably correct but will run for an unacceptably large amount of time (about n^2/2 iterations of the innermost loop for an input n). Try computing the factors from smallest to largest, and divide out each factor as you find it, such as:
for (i = 2; i*i <= n; ++i) {
if (n % i == 0) {
allPrimes.add(i);
while (n % i == 0) n /= i;
}
}
if (n != 1) allPrimes.add(n);
Note that this code will only add prime factors, even without an explicit check for primality.
Almost all the Project Euler problems can be solved using a signed datatype with 64 bits (with the exception of problems that purposefully try to go big like problem 13).
If your going to be working with primes (hey, its project Euler, your going to be working with primes) get a headstart and implement the Sieve of Eratosthenes, Sieve of Atkin, or
Sieve of Sundaram.
One mathematical trick used across many problems is short circuiting finding factors by working to the square root of the target. Anything greater than the square corresponds to a factor less than the square.
You could also speed this up by only checking from 2 to the square root of the target number. Each factor comes in a pair, one above the square root and one below, so when you find one factor you also find it's pair. In the case of the prime test, once you find any factor you can break out of the loop.
Another optimization could be to find the factors before checking that they are prime.
And for very large numbers, it really is faster to experiment with a sieve rather than brute forcing it, especially if you are testing a lot of numbers for primes. Just be careful you're not doing something algorithmically inefficient to implement the sieve (for example, adding or removing primes from lists will cost you an extra O(n)).
Another approach (there is no need to store all primes):
private static boolean isOddPrime(long x) {
/* because x is odd, the even factors can be skipped */
for ( int i = 3 ; i*i <= x ; i+=2 ) {
if ( x % i == 0 ) {
return false;
}
}
return true;
}
public static void main(String[] args) {
long nr = 600851475143L;
long max = 1;
for ( long i = 3; i <= nr ; i+=2 ) {
if ( nr % i == 0 ) {
nr/=i;
if ( isOddPrime(i) ){
max = i;
}
}
}
System.out.println(max);
}
It takes less than 1 ms.

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